Agentic AI — AI systems that can operate autonomously, make decisions, and coordinate complex workflows — is no longer a futuristic concept. In South Africa, the technology is quickly moving from experimental pilot projects into real-world business applications, proving itself indispensable across industries ranging from healthcare to finance.
That’s according to Spatialedge, a leading AI and data science consulting firm and partner of Digicloud Africa, Google’s official reseller enablement partner on the continent.
A Leap Forward for AI in 2025
“AI models have matured a great deal during the past year,” says Pierre le Roux, co-founder and Executive Director of Spatialedge. “As soon as someone experiences working with agents for the first time, it feels magical.”
Over the last year, interest in agentic AI has surged locally and internationally, with enterprises increasingly asking how to deploy the technology to streamline operations and modernize legacy processes.
Instead of chasing the hype around generative AI, Spatialedge’s approach focuses on practical deployment — building agent-based solutions that address specific business problems.
Real-World Use Cases: From Healthcare to Legal and Sales
Spatialedge has already developed agentic AI solutions across several high-impact domains:
-
Healthcare: A medical agent that automates administrative tasks during doctor–patient consultations and files claims seamlessly.
-
Legal: A legal assistant agent that compiles case files, accelerates client responses, and helps secure faster settlements.
-
Sales: A meeting assistant that extracts insights from team discussions and nudges brokers to follow structured sales playbooks.
“These solutions allow human teams to focus on higher-value work,” le Roux explains. “The real magic happens when agents understand context and work continuously in the background.”
The Foundation: Clean Data and Cloud Infrastructure
One of the biggest lessons Spatialedge has learned is that AI success depends on data readiness. “Clean, well-structured data and robust cloud infrastructure separate enterprise-grade AI from everyday consumer tools,” says le Roux.
For example, wealth management firms can now use AI to assess which clients provide value — analyzing portfolio performance, client interactions, and operational costs — all through BigQuery, Google Cloud’s serverless data warehouse. “With the right infrastructure, a self-service analytics agent can be spun up almost instantly,” le Roux notes.
Powered by Google’s AI Ecosystem
Spatialedge relies heavily on Google Cloud technologies to develop and deploy these agents:
-
Google BigQuery for scalable data warehousing
-
Google Agent Development Kit (ADK) for modular AI agent frameworks
-
Vertex AI for fast deployment of ML models
-
Firebase for rapid prototyping of web and mobile apps
-
Gemini Pro 2.5 and NotebookLM for advanced reasoning and knowledge aggregation
This integration enables rapid prototyping — often turning concepts into demos within days — while maintaining enterprise-level security.
The Road Ahead: Ubiquitous, Personal AI Agents
Looking ahead, le Roux envisions a world where AI agents become as ubiquitous as email — seamlessly accessible across every platform and device.
“People will interact with the same agent from Slack, email, WhatsApp, even by voice,” he predicts. “It will know their schedules, understand their context, and deliver answers in the way they prefer.”
Future scenarios might include agents generating daily performance recaps in podcast form during your commute, or solving problems overnight so 80% of the work is done by morning.
The rise of IoT, drones, and meeting transcription technologies means organizations are capturing unprecedented amounts of operational data. Agentic AI will turn this data goldmine into actionable insights — predicting issues, resolving problems, and even initiating support requests without human prompting.
Why It Matters for South Africa
As African enterprises digitize, the shift to agentic AI represents a leapfrog opportunity — enabling local companies to bypass older legacy systems and move directly to context-aware, autonomous AI. This could enhance competitiveness in industries like banking, telecoms, and agriculture, while improving customer experience and operational efficiency.
“Agentic AI is no longer experimental,” le Roux says. “It’s becoming mission-critical — and soon, it will feel strange to work without it.”
